Correlations
Introduction
In order for a company to be successful in the business world they must align their capacity, resources, and material to the expected demand of the products they have to offer. For this reason, companies often use correlation for forecasting the likely consumer demand of their products (CTU Online, 2011). A correlation is a calculation of the connection among two or more variables. Often, when company’s use correlation their intention is to uncover the level at which two or more calculations regarding an equivalent group of components have an inclination of varying together, such as with their consumer demand regarding the products they have to offer (Lanthier, 2002).
Patterns of Correlation
There are basically two patterns in which a correlation of variables can follow. However, a correlation can also be directed as minimal correlation among the variables being examined. With that being said, let us first discuss the two basic patterns, which are positive and negative correlation, which variables can follow when being correlated together. A positive correlation signifies that the variables being examined are moving in an equivalent direction, while a negative correlation signifies that the variables being examined are moving in a contradictory direction. The correlation values among the variables being examined will fluctuate between +1 and -1, but a positive correlation that is just right will be represented with a +1, while a negative correlation will be represented with a -1 among the variables being examined (Lanthier, 2002). Furthermore, when there is no correlation at all among the variables being examined, this will be minimal correlation, and will be represented by 0 (CTU Online, 2011).
Article Findings
Variable A
Variable B
Correlation
Amount of students in school eligible for free lunch program.
Federal and State funding received by school for educational programs.
Positive
Received subsidy impact.
School age students
Positive
Amount of Internet connections in classrooms.
Performance of students as standardized test scores was measured.
Minimal
Internet comfort level of teachers.
Efficiency of teachers using Internet with students.
Negative
In findings related to research report read, the amount of students eligible for the free lunch program and the amount received by the school from federal and state funding for education programs would be a positive correlation, in my opinion. The reason for this is in the article it states the program is aggressing with more funding being continually provided to the educational program, so that in my opinion would mean that the correlation of the two would be continually increasing in the same direction. Next, the received subsidy impact and school age students would also show a positive correlation, but with a continual decrease in the same direction. However, despite the positive correlations of the two previous statements, in the article it states that there is insignificant facts to determine that the program has had an impact on achievements obtained by students measured test scores, so in my opinion, there would be minimal correlation between these two variables. Also, the article states that teachers who are well prepared for the technology and feel comfortable is only reportedly one-third, so this, in my opinion would show a negative correlation increasing in the opposite direction (Goolsbee & Guryan, 2003).
Conclusion
Statistically analyzing the correlation between two are more variables is a way to measure the relationship among the variables. In doing this, the researcher will seek out points that exist already between the variables and conclude on what relationship those known points have in connecting the variables. In addition, the idea of a company utilizing correlation is to permit them to formulate a future statement regarding one variable based upon what is know regarding the other variable (Lanthier, 2002). Also, the article presented for review in determining the correlation among the variables is my opinion as a statistical analyst for Company W.
References
CTU Online. (2011). Applied Managerial Decision Making. Phase 4 course materials [text]. Retrieved from https://campus.ctuonline.edu/pages/MainFrame.aspx?ContentFrame=/Home/Pages/Default.aspx
Goolsbee, A. & Guryan, J. (2003). Closing the digital divide: Internet subsidies in public schools. Retrieved from http://www.chicagobooth.edu/capideas/summer03/digitaldivide.html
Lanthier, E. (2002). Correlation. Retrieved from http://www.nvcc.edu/home/elanthier/methods/correlation.htm